activity
20202026
most citedElastic Net based Feature Ranking and Selection

3 citations · 4 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2026

Information-Theoretic Classifier-Free Guidance with Adaptive Schedule Optimization

Haobo Chen, Xiangxiang Xu, Yuheng Bu

Diffusion models have achieved strong performance in image, text-to-image, and video generation, where conditional generation is often controlled by classifier-free guidance (CFG).…

cs.CL2026

Length Value Model: Scalable Value Pretraining for Token-Level Length Modeling

Zhen Zhang, Changyi Yang, Zijie Xia +11

Tokens are the fundamental units of computation in modern autoregressive models, and generation length directly influences both inference cost and reasoning performance. Despite it…

cs.LG2025

Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective

Firas Laakom, Haobo Chen, Jürgen Schmidhuber +1

Despite substantial progress in promoting fairness in high-stake applications using machine learning models, existing methods often modify the training process, such as through reg…

cs.IT2024

An Algorithm for Computing the Capacity of Symmetrized KL Information for Discrete Channels

Haobo Chen, Gholamali Aminian, Yuheng Bu

Symmetrized Kullback-Leibler (KL) information (\(I_{\mathrm{SKL}}\)), which symmetrizes the traditional mutual information by integrating Lautum information, has been shown as a cr…

cs.LG2023★ 1 cited

Gibbs-Based Information Criteria and the Over-Parameterized Regime

Haobo Chen, Yuheng Bu, Gregory W. Wornell

Double-descent refers to the unexpected drop in test loss of a learning algorithm beyond an interpolating threshold with over-parameterization, which is not predicted by informatio…

cs.LG2020★ 3 cited

Elastic Net based Feature Ranking and Selection

Shaode Yu, Haobo Chen, Hang Yu +5

Feature selection is important in data representation and intelligent diagnosis. Elastic net is one of the most widely used feature selectors. However, the features selected are de…